Publication:
Analysis of JestKOD database using affective state annotations

dc.contributor.coauthorN/A
dc.contributor.departmentN/A
dc.contributor.departmentDepartment of Computer Engineering
dc.contributor.departmentDepartment of Computer Engineering
dc.contributor.kuauthorKeçeci, Sinan
dc.contributor.kuauthorErzin, Engin
dc.contributor.kuauthorYemez, Yücel
dc.contributor.kuprofileMaster Student
dc.contributor.kuprofileFaculty Member
dc.contributor.kuprofileFaculty Member
dc.contributor.otherDepartment of Computer Engineering
dc.contributor.schoolcollegeinstituteGraduate School of Sciences and Engineering
dc.contributor.schoolcollegeinstituteCollege of Engineering
dc.contributor.schoolcollegeinstituteCollege of Engineering
dc.contributor.yokidN/A
dc.contributor.yokid34503
dc.contributor.yokid107907
dc.date.accessioned2024-11-09T23:45:16Z
dc.date.issued2016
dc.description.abstractGesticulation, together with the speech, is an important part of natural and affective human-human interaction. Analysis of gesticulation and speech is expected to help designing more natural human-computer interaction (HCI) systems. We build the JestKOD database, which consists of speech and motion capture recordings of dyadic interactions. In this paper we describe our annotation efforts and present the evaluations that we performed on the annotations of the JestKOD database. These evaluations suggest important findings for usability of the JestKOD database in analysis and modeling of HCI systems.
dc.description.indexedbyWoS
dc.description.indexedbyScopus
dc.description.openaccessYES
dc.description.publisherscopeInternational
dc.identifier.doi10.1109/SIU.2016.7495919
dc.identifier.isbn9781-5090-1679-2
dc.identifier.linkhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84982787194&doi=10.1109%2fSIU.2016.7495919&partnerID=40&md5=e3a18e1ace0eb217e30cf65a31af5f2b
dc.identifier.scopus2-s2.0-84982787194
dc.identifier.urihttp://dx.doi.org/10.1109/SIU.2016.7495919
dc.identifier.urihttps://hdl.handle.net/20.500.14288/13804
dc.identifier.wos391250900235
dc.keywordsAffective state tracking
dc.keywordsAnimation
dc.keywordsComputer-human interaction
dc.keywordsGesticulation
dc.keywordsMachine learning
dc.keywordsSpeech
dc.languageTurkish
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.source2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings
dc.subjectEngineering
dc.subjectElectrical and electronic engineering
dc.titleAnalysis of JestKOD database using affective state annotations
dc.title.alternativeJestKOD veritabanının duygu durum etiketlemelerini kullanarak analizi
dc.typeConference proceeding
dspace.entity.typePublication
local.contributor.authoridN/A
local.contributor.authorid0000-0002-2715-2368
local.contributor.authorid0000-0002-7515-3138
local.contributor.kuauthorKeçeci, Sinan
local.contributor.kuauthorErzin, Engin
local.contributor.kuauthorYemez, Yücel
relation.isOrgUnitOfPublication89352e43-bf09-4ef4-82f6-6f9d0174ebae
relation.isOrgUnitOfPublication.latestForDiscovery89352e43-bf09-4ef4-82f6-6f9d0174ebae

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